Research for discovery and development of new drugs begins with exploration, identification, characterization, and validation of drug targets. Such drug targets are frequently selected from specific cell surface receptors, adhesion molecules, enzymes, substances that participate in intra-cellular transmission of information as is often called signal transduction, intra-nuclear receptors, transcription factors, cytokines, chemokines, inter-cellular substances, etc. Sometimes, specific tissues, organs, and whole animals (that are called experimental disease models when appropriate) as such are chosen as direct drug targets. Thereafter, screening methods are devised for such selected drug targets (wherein applied recently are automation, robotics, high-throughput settings, miniaturization, nanometrics, microfluidics, etc.), chemical libraries of various sources are screened for selected biological activity or non-activity by use of such screening methods (wherein technology of combinatorial chemistry is utilized to construct such chemical libraries when appropriate), so-called “hits” are identified, so-called “lead compounds” are generated by applying various algorithms to such hits, lead compounds are optimized to yield a single or multiple candidate compound(s) by considering so-called “drug-likeness” (for example, as described in Clark, D. E. and Picket, S. D., Drug Discovery Today (2000) 5: 49-58) and biological properties are observed in experimental animal systems. Thereafter, a candidate compound or compounds are formulated in the form of an appropriate preparation (now called a “drug product”) and tested for safety and efficacy in humans, the size of target market and competitive advantage as well as disadvantage of a candidate drug product or products are studied, and, when all existent and foreseeable hurdles are recognized to be overcome by a drug product, an application is filed with a drug regulatory agency in a respective country or region (such as EC) for market release approval of the drug product.
Only after a compound in the form of drug product is approved by a drug regulatory agency of the respective country or region is it placed on sale in the market as a remedy for cure, treatment, or prophylaxis of a particular disease and associated symptoms. (While the term “compound” is used here, this term covers a wide range of substances and includes such biotechnology substances as proteins, enzymes, antibodies, etc. as are not obtained by chemical synthesis, and natural products such as natural antibiotics.) As understood from this description of drug research and development, there exists an enormous number of hurdles for a drug product to clear until it reaches a particular market.
Statistics of seventeen representative Japanese pharmaceutical companies during the period from 1992 to 1996 teach us that the success rate in drug development was one success that reached the market out of 6053 compounds that were synthesized (or obtained) and tested (DATA BOOK, 1999, Japan Pharmaceutical Manufacturers Association). Pharmaceutical industries in the United States of America and European countries also face similar difficulty and hardship in drug research and development. Accordingly, while an enormous number of compounds are synthesized (or prepared by other means) and tested, most of those compounds are dropped during research and development processes. In this specification, these compounds are termed “unsuccessful compounds.”
A significant factor contributing to this low success rate is the difficulty in obtaining an appropriate list of “hit” compounds that would reasonably enable generation of lead compounds. Even if this difficulty is overcome, there is scarce chance of encountering good lead compounds. This would be so even if a validated drug target is identified and the most advanced technologies currently available for drug research such as high throughput screening, structure (/substrate)-based drug design (SBDD) and combinatorial chemistry are employed. While this is due partly to a limitation in the number and diversity of chenes that are proprietary and/or available to a company, a much greater problem arises from the fact that the lack of, or the poorness of, the science which serves to generate lead compounds from a given list of hits and optimize lead compounds to yield a desired drug product. In fact there is a widely recognized tendency where, since the introduction of HTS in drug research, those compounds synthesized in pharmaceutical houses have become greater in size with a significant fraction of compounds exceeding 500 in molecular weight and have demonstrated a tremendous increase in lipophilicity (as determined usually by octanol/water partition coefficient) and an associated decrease in solubility in water even to insolubility, and, as a result, lead compounds are as such difficult to be absorbed from the digestive tract (Lipinsky, C. A., et al., Advanced Drug Delivery Reviews (1997) 23: 3-25) and give little clues to improve and optimize them with respect to “drug-likeness” and other biological characteristics. Furthermore, for example, while many kinds of kinases are known to work in intracellular signal transduction pathways, science is lacking that teaches how to distinguish one kinase working in a specific manner from others that work in different manner and, more importantly, how to interfere with its action with a “drug-like” chene specifically. As a result, pharmaceutical houses are currently forced to repeat so-called random screenings with little confidence or assurance for success in finding a set of good hits or leads. Still another example concerns chenes which modulate protein-protein interactions. Certain people have come to share the view that these chenes need to be much larger in size than those which modulate small molecule ligand-protein interactions. While these large molecule chenes are suitable to interfere with the target protein-protein interactions, they are unable even to pass the cell membrane and reach inside the cell where such interference is needed. Protein-protein interactions are seen frequently in intracellular signal transduction and among transcription factors, and it is known that many pharmaceutical companies have selected these as drug targets. Unless science concerning chene-biological molecule interactions is discovered and advanced, and as long as some ways and means in drug designing methodology are discovered based upon science of such scope, it would be futile to discover a drug that would modulate protein-protein interactions and, accordingly for example, that would interfere with signal transduction pathways and interactions among transcription factors.
Recently, a group of relatively small molecule chenes have been discovered which, by acting in an allosteric manner after attachment, normalize the function of a mutant p53 protein which lacks the ability of the normal p53 protein to bind a specific DNA sequence (Foster, B. A. et al., Science (1999) 286: 2507-2510). This is an example of chenes which interfere with nucleic acid-protein interaction, which may share some degree of similarity to protein-protein interactions in the sense that interacting molecules are large in both cases. This discovery was, however, made as a result of random screening of as many as 100,000 compounds, so the success rate is still quite low.
There is also lack of science which serves to identify an appropriate drug target. As already mentioned, identification of a drug target is the first step in drug research and development. The lack of science in this respect is due largely to the lack of and, if it even exists, the poorness of, the science concerning interactions between chenes and the biological systems. Until chenes can be selected or created based upon the properties known to be possessed by desirable drug compounds, it is impossible to reasonably define the characteristics of a corresponding drug target and retrospectively, based on such characteristics, to construct a legitimate methodology to discover an appropriate drug target.
One of the most important reasons for seeing so many unsuccessful products is the lack of disclosure of data arising from in-house processes of research and development relative to drug products. While information and data concerning successful products and related compounds are frequently disclosed, those concerning unsuccessful compounds are accumulated only within respective houses and are totally unavailable even if people in academia and other pharmaceutical houses want to have access to those data.
Many pharmaceutical companies recently purchased commercially available chemical libraries and use them in screening for biological activities to obtain various data on chenes contained in such libraries. Data, however, are not disclosed and are destined to remain buried within those companies except for findings on certain chenes which have led to successful products. It often happens that different pharmaceutical companies screen chenes of the same commercially available libraries for the same biological activity and share the same failure and error in expectation for success. This constitutes duplication of developmental efforts and costs, and imposes burdens of waste on pharmaceutical companies. Such waste is found not only in pharmaceutical industries but also in other kinds of industries.
It is emphasized here that science is founded and advanced as a result of accumulation of information and data, i.e., facts. Without observations and facts obtained by such observations, any science cannot be founded and advanced. The lack of disclosure of information and data on most of the chenes studied in industries, except for those related to successful products, causes serious limitation to construction and advancement of science concerning chene-biological system interactions. The lack of opportunities for sharing information and data causes not only duplicative waste of efforts and costs in industrial research and development as mentioned in the preceding paragraph, but much more gravely hinders the development of an important branch of science. Science has its highest value in predictive power based on an established scientific rule or rules. Waste of efforts and costs is avoided if a rule or rules are discovered and proven by scientific studies. Science, for example, can give suggestions to what target will be appropriate (conversely, what target is inappropriate), what kind of chenes are desirable for a selected target and how one can find such desirable chenes. This kind of principles apply widely to chene-related industries.